How the signaling networks of individual cells sense and integrate information to determine cell fate remains an important unsolved question. The tumor suppressor protein p53 responds to a wide variety of stresses including DNA damage, hypoxia and hormonal signaling to determine alternative cell fates including cell-cycle arrest, senescence and apoptosis. Recently, my host laboratory has been using long-term time-lapse microscopy to characterize the single-cell dynamics of p53, and discovered that p53 dynamics depend on the type of DNA damage and affect cell fate decisions. Now I plan to combine my training in computation and mass spectrometry with the expertise of my host laboratory to ask how the combined control of p53 dynamics and its signaling network regulate cel fat determination. I wil develop a purification scheme to identify and characterize the signaling profiles of in vivo p53 complex i.e. p53 post-translational modifications and its interacting proteins. In response to gamma-irradiation p53 shows a series of pulses and cells undergo cell cycle arrest. I will examine p53 signaling profiles at different pulses correlated with cell cycle arrest. In contrast, when cells are treated with UV-irradiation or gamma-irradiation plus Nutlin3, cells show similarly a prolonged p53 plus but distinct cell fates. I hypothesize that the modification state of p53 is responsible for these alternate fates, which I will test here. Further I will dissect the functional roles of p53 dynamics, post-translational modifications, and interactin proteins in relation to cell fate determination in single cells. First, flow cytometry will be usedto find correlations between p53 post-translational modifications with the expression of p53 and its targets. Second, I will assess the contribution of specific p53's post-translational modifications/interacting proteins to cel fate choices by introducing mutations on these sites and knocking down p53's interacting proteins. The in vivo p53 dynamics, transcription of its targets, and cell fate markers will then be characterized. The acquired in vivo quantitative data will be used to develop mathematical models for the regulation of p53 transcriptional activity and cell fate determination. The proposed study will provide new insights into the mechanisms by which a cel makes the choice to recover, die or senesce and will be important in helping design efficient and selective cancer therapeutics.